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Cited by 2,010COVID-19 epidemiological studiesCOVID-19 Prevention and ImpactSARS-CoV-2 and COVID-19 Research

The DOI matches its Crossref record; 31 of the 32 references it cites were found in a registry or an index.

An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China.

Open access
Tian, Huaiyu, Liu, Yonghong, Li, Yidan, Wu, Chieh-Hsi, Chen, Bin, Kraemer, Moritz U. G., Li, Bingying, Cai, Jun, Xu, Bo, Yang, Qiqi, Wang, Ben, Yang, Peng, Cui, Yujun, Song, Yimeng, Zheng, Pai, Wang, Quanyi, Bjornstad, Ottar N., Yang, Ruifu, Grenfell, Bryan T., Pybus, Oliver G., Dye, Christopher·2020·Science
DOI 10.1126/science.abb6105PMC PMC7164389

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Abstract

Abstract Respiratory illness caused by a novel coronavirus (COVID-19) appeared in China during December 2019. Attempting to contain infection, China banned travel to and from Wuhan city on 23 January and implemented a national emergency response. Here we evaluate the spread and control of the epidemic based on a unique synthesis of data including case reports, human movement and public health interventions. The Wuhan shutdown slowed the dispersal of infection to other cities by an estimated 2.91 days (95%CI: 2.54-3.29), delaying epidemic growth elsewhere in China. Other cities that implemented control measures pre-emptively reported 33.3% (11.1-44.4%) fewer cases in the first week of their outbreaks (13.0; 7.1-18.8) compared with cities that started control later (20.6; 14.5-26.8). Among interventions investigated here, the most effective were suspending intra-city public transport, closing entertainment venues and banning public gatherings. The national emergency response delayed the growth and limited the size of the COVID-19 epidemic and, by 19 February (day 50), had averted hundreds of thousands of cases across China. One sentence summary Travel restrictions and the national emergency response delayed the growth and limited the size of the COVID-19 epidemic in China.

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Figures

Fig. 1 Dates of discovery of the novel coronavirus causing COVID-19 and of the implementation of control measures in China, from 31 December 2019.
Fig. 1 Dates of discovery of the novel coronavirus causing COVID-19 and of the implementation of control measures in China, from 31 December 2019.CC BY · PubMed Central
Fig. 2 The dispersal of COVID-19 in China 15 days before and 25 days after the Spring Festival (Chinese Lunar New Year). (A) Movement outflows from Wuhan city during Spring Festival travel in 2017, 2018, and 2020. The vertical dotted line is the date of the Spring Festival (Chinese Lunar New Year). (B) The number of recorded movements from Wuhan city to other provinces during the 15 days before the Spring Festival in 2020. The shading from light to dark represents the number of human movements from Wuhan to each province. The areas of circles represent the cumulative number of cases reported by 30 January 2020, 1 week after the Wuhan travel ban on 23 January. (C) Association between the cumulative number of confirmed cases reported before 30 January and the number of movements from Wuhan to other provinces.
Fig. 2 The dispersal of COVID-19 in China 15 days before and 25 days after the Spring Festival (Chinese Lunar New Year). (A) Movement outflows from Wuhan city during Spring Festival travel in 2017, 2018, and 2020. The vertical dotted line is the date of the Spring Festival (Chinese Lunar New Year). (B) The number of recorded movements from Wuhan city to other provinces during the 15 days before the Spring Festival in 2020. The shading from light to dark represents the number of human movements from Wuhan to each province. The areas of circles represent the cumulative number of cases reported by 30 January 2020, 1 week after the Wuhan travel ban on 23 January. (C) Association between the cumulative number of confirmed cases reported before 30 January and the number of movements from Wuhan to other provinces.CC BY · PubMed Central
Fig. 3 Spatial dispersal of COVID-19 in China. (A) Cumulative number of cities reporting cases by 19 February 2020. Arrival days are defined as the time interval (days) from the date of the first case in the first infected city (Wuhan) to the date of the first case in each newly infected city (a total of 324 cities), to characterize the intercity transmission rate of COVID-19. The dashed line indicates the date of the Wuhan travel ban (shutdown). (B) Before (blue) and after (red) the intervention by 30 January 2020, 1 week after the Wuhan travel ban (shutdown). The blue line and points show the fitted regression of arrival times up to the shutdown on day 23 (23 January, vertical dashed line). Gray points show the expected arrival times after day 23, without the shutdown. The red line and points show the fitted regression of delayed arrival times after the shutdown on day 23. Each observation (point) represents one city. Error bars give ±2 standard deviations.
Fig. 3 Spatial dispersal of COVID-19 in China. (A) Cumulative number of cities reporting cases by 19 February 2020. Arrival days are defined as the time interval (days) from the date of the first case in the first infected city (Wuhan) to the date of the first case in each newly infected city (a total of 324 cities), to characterize the intercity transmission rate of COVID-19. The dashed line indicates the date of the Wuhan travel ban (shutdown). (B) Before (blue) and after (red) the intervention by 30 January 2020, 1 week after the Wuhan travel ban (shutdown). The blue line and points show the fitted regression of arrival times up to the shutdown on day 23 (23 January, vertical dashed line). Gray points show the expected arrival times after day 23, without the shutdown. The red line and points show the fitted regression of delayed arrival times after the shutdown on day 23. Each observation (point) represents one city. Error bars give ±2 standard deviations.CC BY · PubMed Central
Fig. 4 The role of interventions in controlling the COVID-19 outbreak across China. (A) Epidemic model (line) fitted to daily reports of confirmed cases (points) summed across 31 provinces. Hubei excludes Wuhan city. (B) Expected epidemic trajectories without the Wuhan travel ban (shutdown), and with (blue) or without (red) interventions carried out as part of the Level 1 national emergency response, with the Wuhan travel ban and with (black) or without (orange) the intervention. Vertical dashed lines in (A) and (B) mark the date of the Wuhan travel ban and the start of the emergency response on 23 January. Shaded regions in (A) and (B) mark the 95% prediction envelopes.
Fig. 4 The role of interventions in controlling the COVID-19 outbreak across China. (A) Epidemic model (line) fitted to daily reports of confirmed cases (points) summed across 31 provinces. Hubei excludes Wuhan city. (B) Expected epidemic trajectories without the Wuhan travel ban (shutdown), and with (blue) or without (red) interventions carried out as part of the Level 1 national emergency response, with the Wuhan travel ban and with (black) or without (orange) the intervention. Vertical dashed lines in (A) and (B) mark the date of the Wuhan travel ban and the start of the emergency response on 23 January. Shaded regions in (A) and (B) mark the 95% prediction envelopes.CC BY · PubMed Central

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Metadata

Authors
Tian, H., Liu, Y., Li, Y., Wu, C.-H., Chen, B., Kraemer, M. U. G., Li, B., Cai, J., Xu, B., Yang, Q., Wang, B., Yang, P., Cui, Y., Song, Y., Zheng, P., Wang, Q., Bjornstad, O. N., Yang, R., Grenfell, B. T., Pybus, O. G., & Dye, C.
Affiliations
  • Beijing Normal University (CN)
  • University of Southampton (GB)
  • Department of Land, Air and Water Resources, University of California Davis, Davis, CA, USA.
  • Boston Children's Hospital (US)
  • Tsinghua University (CN)
  • Beijing Center for Disease Prevention and Control (CN)
  • Beijing Institute of Microbiology and Epidemiology (CN)
  • University of Hong Kong (HK)
  • Peking University (CN)
  • Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA, USA.
  • National Institutes of Health (US)
  • University of Oxford (GB)
Corresponding author
  • Tian, Huaiyu
  • Yang, Ruifu
  • Grenfell, Bryan T.
  • Pybus, Oliver G.
  • Dye, Christopher
ORCID
Venue
Science
Publisher
American Association for the Advancement of Science (AAAS)
Published
2020-05-08
Volume
368
Issue
6491
Pages
638-642
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
DOI
10.1126/science.abb6105
PMC
PMC7164389
OpenAlex
W3013188135
Cited by
2,010
References
32
Citations by year
2026: 45 · 2025: 75 · 2024: 129 · 2023: 214 · 2022: 386 · 2021: 627 · 2020: 532
FWCI
70.26
Type
journal article
Language
en
Open access
Licence
Locations
  • Science (publishedVersion, cc-by)
  • medRxiv (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • The HKU Scholars Hub (University of Hong Kong) (publishedVersion)
  • ePrints Soton (University of Southampton) (acceptedVersion)
  • Greater South Information System
Funders
  • National Natural Science Foundation of China (81673234)
  • Young Elite Scientist Sponsorship Program by CAST (2018QNRC001)
  • Beijing Natural Science Foundation (JQ18025)
  • Beijing Advanced Innovation Program for Land Surface Science (None)
Topics
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Social Sciences › Sociology and Political Science › COVID-19 Prevention and Impact
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
Keywords
COVID-19 pandemic, Wuhan lockdown, public health interventions, epidemic spread, human mobility
MeSH terms
Betacoronavirus, COVID-19, SARS-CoV-2, China, Communicable Disease Control, Humans, Pneumonia, Viral, Regression Analysis, Travel, Models, Statistical, Public Health Practice, Incidence, Coronavirus Infections, Epidemics, Pandemics

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